Control system, air conditioning system, control method, and program

Abstract

The present invention provides on-timer operation which makes it possible to achieve both comfort and low power consumption. Provided is a control system for controlling an air conditioner, said control system comprising: a setting reception unit which receives settings for a target temperature and a specified time when the target temperature should be achieved; an optimal operation calculation unit which calculates time-series air conditioning capacity of the air conditioner such that power used by the air conditioner to achieve the target temperature at the specified time is minimized; and a control unit which operates the air conditioner on the basis of the time-series air conditioning capacity

Description

Technical Field

[0001] The present disclosure relates to a control system, an air conditioning system, a control method, and a program. The present disclosure claims priority based on Japanese Patent Application No. 2023-131587, filed in Japan on August 10, 2023, the content of which is incorporated herein by reference.Background Art

[0002] A function called an on-timer operation is provided, in which the air conditioner is automatically started before a specified time designated by a user, and cooling operation or heating operation is performed such that a room temperature reaches a target temperature by the specified time. By using the on-timer operation, for example, the user can designate a return time as the specified time, and the air conditioning of the house can be performed to a desired target temperature at the time of returning home. PTL 1 discloses an air conditioning system that generates a building load prediction model by learning an indoor temperature, an outside air temperature, and an air conditioning capacity exhibited by an air conditioner, inputs a predicted value of the indoor temperature, the air conditioning capacity, and the outside air temperature at the specified time at the time of determining an air conditioning start time to the building load prediction model to predict a building load, determines a pre-operation start time in 5-minute increments in a range of 0 to 40 minutes before the specified time according to the predicted building load, and starts the operation at the determined pre-operation start time. According to the air conditioning system of PTL 1, for a room having a large building load, the air conditioning can be automatically started earlier than for a room having a small building load, so that the possibility that the temperature of the room does not reach the target temperature by the specified time even in a case where the on-timer operation is performed in a case where the building load is large can be reduced. However, even in a case where the target temperature can be achieved by this control, for example, the air conditioning may be started earlier than necessary, which may increase the power consumption.Citation ListPatent Literature

[0003] [PTL 1] Japanese Unexamined Patent Application Publication No. 2020-125868Summary of InventionTechnical Problem

[0004] In the on-timer operation, a control method that can achieve both comfort and low power consumption is required.

[0005] The present disclosure provides a control system, an air conditioning system, a control method, and a program that can solve the above-described problems.Solution to Problem

[0006] According to an aspect of the present disclosure, a control system for controlling an air conditioner includes a setting receiving unit that receives a setting of a target temperature and a specified time at which the target temperature is to be achieved, an optimal operation calculation unit that calculates time-series air conditioning capacity of the air conditioner such that power consumption of the air conditioner for achieving the target temperature at the specified time is minimized, and a control unit that operates the air conditioner based on the time-series air conditioning capacity.

[0007] According to another aspect of the present disclosure, an air conditioning system includes an air conditioner and the control system.

[0008] According to still another aspect of the present disclosure, a control method of an air conditioner includes a step of receiving a setting of a target temperature and a specified time at which the target temperature is to be achieved, a step of calculating time-series air conditioning capacity of the air conditioner such that power consumption of the air conditioner for achieving the target temperature at the specified time is minimized, and a step of operating the air conditioner based on the time-series air conditioning capacity.

[0009] According to still another aspect of the present disclosure, a program causing a computer to execute a step of receiving a setting of a target temperature and a specified time at which the target temperature is to be achieved, a step of calculating time-series air conditioning capacity of the air conditioner such that power consumption of the air conditioner for achieving the target temperature at the specified time is minimized, and a step of operating the air conditioner based on the time-series air conditioning capacity.Advantageous Effects of Invention

[0010] According to the control system, the air conditioning system, the control method, and the program described above, the target temperature can be achieved with low power consumption by the specified time.Brief Description of Drawings

[0011] FIG. 1 is a diagram showing an example of an air conditioning system according to an embodiment. FIG. 2 is a diagram showing an example of a room temperature prediction model according to the embodiment. FIG. 3 is a block diagram showing a detailed configuration example of an optimal operation calculation unit according to the embodiment. FIG. 4A is a first diagram for describing a method of calculating an optimal air conditioning capacity according to the embodiment. FIG. 4B is a second diagram for describing the method of calculating the optimal air conditioning capacity according to the embodiment. FIG. 5 is a flowchart showing an example of control of an on-timer operation according to the embodiment. FIG. 6 is a diagram showing an example of a hardware configuration of the air conditioning system in the embodiment. Description of Embodiments<Embodiment>

[0012] Hereinafter, a control method of an on-timer operation according to the embodiment of the present disclosure will be described with reference to FIGS. 1 to 6.(Configuration of Air Conditioning System)

[0013] FIG. 1 is a diagram showing an example of an air conditioning system according to an embodiment. As shown in FIG. 1, an air conditioning system 100 includes an air conditioner 1, a server 20, and a user terminal 30. The air conditioner 1 includes an outside air temperature sensor 2, an indoor temperature sensor 3, a compressor 4, and a control device 10. For example, the outside air temperature sensor 2 is provided in an outdoor unit (not shown), and the indoor temperature sensor 3 is provided in an indoor unit (not shown), but the installation locations of the outside air temperature sensor 2 and the indoor temperature sensor 3 are not limited thereto. The outside air temperature sensor 2 and the indoor temperature sensor 3 are connected to the control device 10, and the control device 10 acquires temperatures measured by the outside air temperature sensor 2 and the indoor temperature sensor 3. The compressor 4 and the control device 10 are connected to each other, and the control device 10 controls the compressor 4 and detects an operation state of the compressor 4. For example, the control device 10 can operate the compressor 4 at a desired rotation speed and can detect the rotation speed thereof. The server 20 creates a room temperature prediction model used to calculate an air conditioning start time of the on-timer operation. The user terminal 30 is a smartphone or the like owned by a user of the air conditioner 1, and the user can perform a setting of the target temperature and the specified time in the on-timer operation, an execution instruction of the on-timer operation, and the like from the user terminal 30. The control device 10, the server 20, and the user terminal 30 are communicably connected to each other via a network NW.(Configuration of Control Device)

[0014] The control device 10 includes a sensor information acquisition unit 11, a setting receiving unit 12, an optimal operation calculation unit 13, a control unit 14, and a communication unit 15.

[0015] The sensor information acquisition unit 11 acquires an outside air temperature measured by the outside air temperature sensor 2 and an indoor temperature measured by the indoor temperature sensor 3.

[0016] The setting receiving unit 12 receives settings of a target temperature of an air conditioning target space and a specified time at which the target temperature is to be achieved, and the like. For example, the target temperature and the specified time are set by using a remote controller (not shown) or the user terminal 30.

[0017] The optimal operation calculation unit 13 calculates a time (referred to as an arrival time) until the indoor temperature of the air conditioning target space reaches the target temperature and an air conditioning capacity required at that time. The air conditioning capacity is a strength of heating or cooling exhibited by the air conditioner 1. The air conditioning capacity has a positive correlation with power used for air conditioning by the air conditioner 1, and can be calculated from, for example, a rotation speed of the compressor 4. The optimal operation calculation unit 13 calculates a transition of time-series air conditioning capacity such that the target temperature can be achieved by the specified time with the lowest power consumption based on a room temperature prediction model 131 created by a room temperature prediction model creation unit 21 described below and the outside air temperature, the indoor temperature, and the like measured by the air conditioner 1, and calculates the arrival time from the result. The optimal operation calculation unit 13 converts the time-series air conditioning capacity into a rotation speed of the compressor 4 to calculate a time-series rotation speed of the compressor 4 for achieving the target temperature by the specified time with the lowest power consumption. Further, the optimal operation calculation unit 13 predicts a transition of time-series indoor temperature in a case where the target temperature can be achieved by the specified time with the lowest power consumption, and provides the user with the prediction of the indoor temperature transition during the on-timer operation by transmitting the prediction to the user terminal 30.

[0018] The control unit 14 controls the compressor 4 and the like to execute air conditioning. During the on-timer operation, the control unit 14 starts the operation of the compressor 4 and the like an arrival time before the specified time set by the user, which is calculated by the optimal operation calculation unit 13, operates the compressor 4 according to the time-series rotation speed of the compressor 4 calculated by the optimal operation calculation unit 13, and performs cooling operation or heating operation.

[0019] The communication unit 15 communicates with the server 20 and the user terminal 30. For example, as learning data required for creating the room temperature prediction model 131, the communication unit 15 transmits the outside air temperature and the indoor temperature which are acquired by the sensor information acquisition unit 11, the rotation speed of the compressor 4 which is detected by the control unit 14, and the specified time and the target temperature which are acquired by the setting receiving unit 12, to the server 20. The communication unit 15 acquires the room temperature prediction model 131 and the like from the server 20. The communication unit 15 acquires the target temperature, the specified time, and the like transmitted from the user terminal 30.(Configuration of Server)

[0020] The server 20 includes the room temperature prediction model creation unit 21 and a communication unit 22.

[0021] The room temperature prediction model creation unit 21 creates the room temperature prediction model 131 for predicting the arrival time required to set the indoor temperature of the air conditioning target space to the target temperature. The room temperature prediction model 131 creates a prediction model that receives the indoor temperature (K), the outside air temperature (K), and the air conditioning capacity (W / m 2< ) and outputs a future indoor temperature. FIG. 2 shows an example of the room temperature prediction model 131.(Room Temperature Prediction Model)

[0022] An Auto-Regressive with eXogenous model (ARX model) shown in FIG. 2 is a linear multiple regression model showing a relationship among an indoor temperature T in (k) at a certain control step k, a deviation T O-in (k) obtained by subtracting the indoor temperature T in (k) from an outside air temperature To(k), and an air conditioning capacity φ h (k). When the ARX model of FIG. 2 is arranged, the following expression (1) is obtained.

[0023] The room temperature prediction model creation unit 21 calculates coefficients a 1 , a 2 , ..., a m , b 11 , b 12 , ..., b 1m , b 21 , b 22 , ..., b 2m of the expression (1), a bias term w 0 , which is a constant representing noise or disturbance, and a step length m that can maintain a high prediction accuracy, using past operation data of the air conditioner 1, that is, the outside air temperature measured by the outside air temperature sensor 2, the indoor temperature measured by the indoor temperature sensor 3, and the rotation speed of the compressor 4 instructed by the control unit 14, which are collected at a predetermined cycle in a past predetermined period. The rotation speed of the compressor 4 can be converted into an air conditioning capacity (W / m 2< ) by the following expressions (2) to (4).

[0024] During heating operation, when the outside air temperature T O is in the frost-free temperature region (T O ≤ -7°C or 5.5°C < T O ) φ h T O = φ − 7 + φ 7 − φ − 7 ÷ 7 − − 7 × T O − − 7

[0025] During heating operation, when the outside air temperature T O is in the frost temperature region (-7°C < T O ≤ 5.5°C) φ h T O = φ − 7 + φ 2 − φ − 7 ÷ 2 − − 7 × T O − − 7

[0026] Here, φ(-7), φ(2), and φ(7) are air conditioning capacities at outside air temperatures of -7°C, 2°C, and 7°C, respectively.

[0027] In case of cooling operation φ h T O = φ 35 + φ 29 − φ 35 ÷ 35 − 29 × 35 − T O

[0028] Here, φ(35) and φ(29) are air conditioning capacities at outside air temperatures of 35°C and 29°C, respectively.

[0029] In a case where the rotation speed of the compressor 4 is ncmp and K1, K2, K3, K4, and K5 are predetermined constants, the relationship between ncmp and φ(-7), φ(2), φ(7), φ(29), and φ(35) is as follows.

[0030] The room temperature prediction model creation unit 21 converts the rotation speed of the compressor 4 into φ(-7), φ(2), φ(7), φ(29), and φ(35) by the expression (4), and converts the rotation speed of the compressor 4 into the air conditioning capacity φ h (T O ) by using any of the expression (2), the expression (2'), and the expression (3) according to the outside air temperature T O .

[0031] For example, the room temperature prediction model creation unit 21 may calculate the coefficients a 1 , and the like by a least-squares method so as to minimize a square of a difference (RMSE: Root Mean Squared Error) between a measured value of an actual indoor temperature included in the operation data of the air conditioner 1 and a predicted value of the indoor temperature obtained by substituting the measured value of the actual indoor temperature, a measured value of the outside air temperature, and an air conditioning capacity calculated from the rotation speed of the compressor 4 included in the operation data into the expression (1). Alternatively, in a case where appropriate values of the coefficients a 1 , and the like cannot be calculated by the least-squares method due to multicollinearity between explanatory variables or in a case where overfitting occurs, the coefficients a 1 , and the like may be calculated by ridge regression. In a case where a matrix of input data is X, a matrix of output data is Y, and a matrix of coefficients is W, the least-squares method obtains the coefficients W by W = (X T< X) -1< X T< Y, but the ridge regression obtains the coefficients W by W = (X T< X - dI) -1< X T< Y using a unit matrix I. In a case where the coefficients a 1 , and the like are calculated by the ridge regression, the room temperature prediction model creation unit 21 appropriately sets a parameter d of the ridge regression in addition to the step length m to calculate the coefficients a 1 , and the like. For example, various values may be set for m and d, the coefficients a 1 , and the like may be calculated for each combination of m and d, and m and d with the minimum RMSE may be adopted from among the calculated coefficients. A method of calculating the coefficients a 1 , and the like is not limited to the above, and any other method can be used. It is preferable to use the operation data of the air conditioner 1 installed in the actual air conditioning target space as the time-series data of the indoor temperature, the outside air temperature, and the rotation speed of the compressor 4 used as the learning data, but the present disclosure is not limited thereto. For example, the operation data of another air conditioner having the same capacity as the air conditioner 1 provided in a space having the same property as the air conditioning target space may be used. In a case where the coefficients a 1 , and the like are calculated, the room temperature prediction model creation unit 21 applies the calculated coefficients a 1 , and the like to the expression (1) to create the room temperature prediction model 131.

[0032] The communication unit 22 communicates with the control device 10 and the like. For example, the communication unit 22 receives the indoor temperature, the outside air temperature, the rotation speed of the compressor 4, and the like from the control device 10, and outputs these values to the room temperature prediction model creation unit 21. The room temperature prediction model creation unit 21 stores and accumulates these data as the learning data for calculating the coefficients a 1 , and the like. The communication unit 22 transmits the room temperature prediction model 131 created by the room temperature prediction model creation unit 21 to the control device 10.

[0033] The user terminal 30 is a portable terminal such as a smartphone owned by the user of the air conditioner 1. The user operates the user terminal 30 to set the target temperature or the specified time and to issue an instruction to perform the on-timer operation. Then, the user terminal 30 transmits the setting information and the instruction information to the control device 10 of the air conditioner 1.

[0034] The configuration illustrated in FIG. 1 is an example. For example, the optimal operation calculation unit 13 may be provided in the server 20 to perform processing with a large amount of calculation by the server 20, such as transmitting the calculation result to the control device 10, or the room temperature prediction model creation unit 21 may be provided in the control device 10. The room temperature prediction model creation unit 21 may receive information on the humidity and the solar radiation amount, and create the room temperature prediction model 131 by learning the time-series data of the indoor temperature, the outside air temperature, the rotation speed of the compressor 4, the humidity, and the solar radiation amount.(Details of Optimal Operation Calculation)

[0035] FIG. 3 shows a detailed configuration example of the optimal operation calculation unit 13. As shown in the drawing, the optimal operation calculation unit 13 includes an optimal air conditioning capacity calculation unit 132, an optimal indoor temperature calculation unit 133, and an optimal rotation speed calculation unit 134. The optimal air conditioning capacity calculation unit 132 has a solver that solves a linear programming problem or the room temperature prediction model 131, receives upper and lower limit values of the air conditioning capacity, the outside air temperature, the indoor temperature, the target temperature, and a time (time until the on-timer operation) until the specified time as input data, analyzes which air conditioning operation can achieve the target temperature with the lowest power consumption by the specified time, and calculates the time-series air conditioning capacity (power consumption per unit time) and the arrival time in this case. The functions of the optimal air conditioning capacity calculation unit 132 will be specifically described with reference to FIGS. 4A and 4B.

[0036] For example, it is assumed that m = 1 is obtained as the step length having a high prediction accuracy of the indoor temperature. In this case, when the expression (1) is arranged, the following expression (1') is obtained. T in k + 1 = a 1 T in k + b 11 φ h k + b 21 T O k + w 0

[0037] The coefficients a 1 , and the like of the expression (1') are not exactly the same as the coefficients a 1 , and the like of the expression (1), and for example, in a case of the coefficient a 1 , the expression (1) is replaced with To - T in for T o-in , arranged, and then replaced with, for example, (a 1 - b 21 ) as a 1 . In the expression (1'), T in is the indoor temperature, φ h is the heating capacity, T O is the outside air temperature, and w O is the bias term. The expression (1') is an example of the room temperature prediction model 131 included in the optimal air conditioning capacity calculation unit 132. In a case where the heating capacity φ h and the outdoor temperature T O are given until N - 1 minutes later, the room temperature T in until N minutes later can be represented by an expression (5) of FIG. 4A.

[0038] The optimal air conditioning capacity calculation unit 132 calculates an optimal heating capacity φ h that satisfies upper and lower limit values of the heating capacity and the target temperature T min and minimizes a total of the heating capacity until the target temperature T min is achieved by solving a linear programming problem (expression (6)) shown in FIG. 4B using the expression (5). The expression (6) is an expression in a case where the heating operation is performed by the on-timer operation and the target temperature is achieved by the specified time, as an example, and a linear programming problem can be formulated in the same manner in a case of the cooling operation. In the expression (6), c represents a 1 × N matrix in which all elements are 1, φ min represents a lower limit value of the heating capacity, and φ max represents an upper limit value of the heating capacity. φ min and φ max are optionally set by a designer or the like. "minimize" represents that an objective function c T< φ h is minimized (the heating capacity is minimized), and "subject to" represents a constraint. The first constraint from the top is a constraint that the heating capacity is equal to or greater than the lower limit value φ min , the second constraint is a constraint that the heating capacity is equal to or smaller than the upper limit value φ max , and the third constraint, using expression (5), is a constraint that the future indoor temperature is equal to or greater than T min (in a case of cooling, it is set to be equal to or smaller than T min ). For example, in a case where the target temperature is T SP (°C) and the indoor temperature reaches T SP (°C) after M (<N) minutes (M minutes is the target time), the room temperature lower limit T min that the future indoor temperature is to satisfy is set as follows. T min = 0 , … , 273.15 + T sp , … , 273.15 + T sp T

[0039] Here, in a case where the length of one control step is set to, for example, 1 minute, the first 0 of the matrix T min indicates the room temperature lower limit to be satisfied after 1 minute, and in this example, M zeros are arranged from the beginning. Then, 273.15 + T sp (K) is set in the (M + 1)-th to N-th elements. By setting in this way and solving the linear programming problem of the expression (6), the heating capacity per minute in a case where the indoor temperature T sp (°C) is achieved after M minutes and the power consumption is minimized can be calculated. For example, the optimal operation calculation unit 13 uses the indoor temperature measured by the indoor temperature sensor 3 at the time of prediction (at the time of starting to solve the linear programming problem) as an initial value T in (0) of the indoor temperature, uses 0 as an initial value φ h (0) of the heating capacity, uses the outside air temperature measured by the outside air temperature sensor 2 at the time of prediction as an initial value T O (0) of the outside air temperature, predicts the indoor temperature after 1 minute by the expression (1'), sets any value to the heating capacity φ h (1) after 1 minute, uses the indoor temperature after 1 minute predicted by the expression (1') as the indoor temperature T in (1), uses the outside air temperature at the time of prediction as the indoor temperature T O (1) after 1 minute as it is, predicts the indoor temperature after 2 minutes by the expression (1'), and repeats the same calculation for the subsequent time to search for a time-series combination of indoor temperature T in , outside air temperature T O , and heating capacity φ h satisfying the expression (6). As a method of efficiently searching for a time-series combination of T in , To, and φ h satisfying the expression (6), a simplex method, an interior point method, and the like are known. The optimal operation calculation unit 13 solves the linear programming problem of FIG. 4B by using, for example, the simplex method or the interior point method. In a case where the linear programming problem is solved, for example, the heating capacity per minute from the time of prediction to N minutes later is obtained. φ h = 0 , 0 , 0 , φ h 1 , φ h 2 , φ h 3 , …

[0040] For example, it is assumed that a calculation result such as the expression (7) is obtained. A time slot in which the heating capacity is 0 is a time slot in which the operation is not performed, and a time corresponding to the control step in which a value greater than 0 is set is the operation start time in the on-timer operation. In a case of the expression (7), it is shown that the air conditioner 1 is stopped until 2 minutes later (the first 0 indicates that the heating capacity is 0 after 0 minutes, the second 0 indicates that the heating capacity is 0 after 1 minute, and the third 0 indicates that the heating capacity is 0 after 2 minutes), the operation of the air conditioner 1 is started at the heating capacity φ h1 after 3 minutes, the operation is performed at the heating capacity φ h2 after 4 minutes, the operation is performed at the heating capacity φ h3 after 5 minutes, and the like, and the indoor temperature T sp (°C) is achieved after M minutes while minimizing the power consumption. The optimal operation calculation unit 13 solves the linear programming problem illustrated in the expression (6) to calculate the time-series air conditioning capacity (for example, the expression (7)), and outputs this data to the optimal indoor temperature calculation unit 133 and the optimal rotation speed calculation unit 134. The time-series air conditioning capacity calculated by the optimal operation calculation unit 13 is referred to as the optimal air conditioning capacity.

[0041] The optimal indoor temperature calculation unit 133 has the room temperature prediction model 131. In a case where the optimal air conditioning capacity is input, the optimal indoor temperature calculation unit 133 inputs the optimal air conditioning capacity, the outside air temperature at the time of prediction, and the indoor temperature at the time of prediction to the room temperature prediction model 131 (the indoor temperature at the time of prediction is input as the initial value of the indoor temperature, and the outside air temperature is input as the outside air temperature at each time after the time of prediction), and predicts the indoor temperature for each control step until M minutes later (or until N minutes later) by the room temperature prediction model 131. As a result, for example, the transition of the indoor temperature per minute from the current time (time of prediction) to the specified time is predicted. The time-series indoor temperature predicted in this way is referred to as the optimal indoor temperature. The optimal indoor temperature calculation unit 133 transmits the optimal indoor temperature to the user terminal 30 through the communication unit 15. The user terminal 30 acquires the optimal indoor temperature and displays the optimal indoor temperature on a display unit. As a result, the user can check the prediction of the transition of the indoor temperature for the on-timer operation instructed by the user.

[0042] In a case where the optimal air conditioning capacity is input, the optimal rotation speed calculation unit 134 converts the optimal air conditioning capacity into a time-series rotation speed of the compressor 4 (referred to as an optimal rotation speed of the compressor), and outputs the converted rotation speed to the control unit 14. The optimal rotation speed calculation unit 134 calculates the rotation speed of the compressor 4 by reverse calculation from the air conditioning capacity by using the expressions (2) to (4), and converts the time-series air conditioning capacity into the time-series rotation speed of the compressor 4. In a case where the on-timer operation is set, the control unit 14 controls the compressor 4 based on the optimal rotation speed of the compressor (for example, the expression (7)) acquired from the optimal rotation speed calculation unit 134. The control unit 14 may control the compressor 4 as the optimal rotation speed of the compressor, or may correct the optimal rotation speed of the compressor by deviation feedback control (for example, PID control or PI control) such that a difference between the optimal indoor temperature and the actual indoor temperature is close to 0, and then control the compressor 4 by using the corrected rotation speed.(Operation)

[0043] Next, an operation of the air conditioning system 100 according to the present embodiment will be described with reference to FIG. 5.

[0044] FIG. 5 is a flowchart showing an example of control of an on-timer operation according to the embodiment.

[0045] First, the room temperature prediction model creation unit 21 creates the room temperature prediction model 131 (step S11). The room temperature prediction model creation unit 21 creates the room temperature prediction model 131 based on the past operation data of the air conditioner 1, for example, the time-series of indoor temperature, outside air temperature, and rotation speed of the compressor 4, and the ARX model illustrated in FIG. 2. The room temperature prediction model creation unit 21 transmits the created room temperature prediction model 131 to the control device 10 through the communication unit 22. In the control device 10, the optimal operation calculation unit 13 acquires and stores the transmitted room temperature prediction model 131.

[0046] Next, the user sets the operation mode (cooling operation or heating operation), the target temperature, and the specified time to the control device 10 by using the user terminal 30, a remote controller (not shown), or the like, and issues an instruction to perform the on-timer operation (step S12). The setting receiving unit 12 acquires the operation mode, the target temperature, the specified time, and the instruction to execute the on-timer operation through the communication unit 15, and outputs these pieces of information to the optimal operation calculation unit 13.

[0047] Next, the optimal operation calculation unit 13 calculates the optimal air conditioning capacity by using the optimal air conditioning capacity calculation unit 132 (step S13). The optimal air conditioning capacity calculation unit 132 acquires the outside air temperature measured by the outside air temperature sensor 2, the indoor temperature measured by the indoor temperature sensor 3, the target temperature and the specified time set by the user, and the upper and lower limit values of the air conditioning capacity, and calculates the optimal air conditioning capacity by solving the linear programming problem as illustrated in FIG. 4B. The upper and lower limit values of the air conditioning capacity are set in advance, and the optimal operation calculation unit 13 stores these values. The optimal air conditioning capacity calculation unit 132 outputs the optimal air conditioning capacity to the optimal indoor temperature calculation unit 133 and the optimal rotation speed calculation unit 134.

[0048] Next, the optimal operation calculation unit 13 calculates the optimal indoor temperature by using the optimal indoor temperature calculation unit 133 (step S14). The optimal indoor temperature calculation unit 133 inputs the outside air temperature measured by the outside air temperature sensor 2, the indoor temperature measured by the indoor temperature sensor 3, and the initial value of the air conditioning capacity to the room temperature prediction model 131 (for example, the expression (1')), and predicts the indoor temperature after one control step. The optimal indoor temperature calculation unit 133 inputs the outside air temperature measured by the outside air temperature sensor 2, the predicted value of the indoor temperature after one control step, and the air conditioning capacity after one control step based on the optimal air conditioning capacity to the expression (1'), and predicts the indoor temperature after two control steps. For three or more control steps, the optimal indoor temperature calculation unit 133 also inputs the predicted indoor temperature and the air conditioning capacity designated by the optimal air conditioning capacity to the room temperature prediction model 131 to sequentially predict the future indoor temperature for each control step.

[0049] Next, the optimal operation calculation unit 13 notifies the user of the optimal indoor temperature (step S15). The optimal operation calculation unit 13 transmits the optimal indoor temperature calculated by the optimal indoor temperature calculation unit 133 to the user terminal 30 through the communication unit 15. The user terminal 30 receives the optimal indoor temperature and outputs the received optimal indoor temperature to the display unit. As a result, the user can understand how the indoor temperature transitions to the target temperature by the on-timer operation. The optimal indoor temperature may be transmitted to the remote controller (not shown), and the display unit of the remote controller may display the prediction of the transition of the indoor temperature.

[0050] Next, the optimal operation calculation unit 13 calculates the optimal rotation speed of the compressor by using the optimal rotation speed calculation unit 134 (step S16). The optimal rotation speed calculation unit 134 converts the optimal air conditioning capacity acquired from the optimal air conditioning capacity calculation unit 132 into the rotation speed of the compressor 4 by using the expressions (2) to (4) to calculate the optimal rotation speed of the compressor. The optimal operation calculation unit 13 outputs the optimal rotation speed of the compressor to the control unit 14.

[0051] Next, the control unit 14 starts the air conditioning (step S17). The control unit 14 controls a refrigerant circuit (not shown) such that the air conditioning can be performed in the operation mode designated in the on-timer operation, and starts the air conditioning based on the optimal rotation speed of the compressor. The optimal rotation speed of the compressor is set to, for example, the rotation speed of the compressor 4 per minute from the current time (time of prediction) to N minutes later. The control unit 14 starts the air conditioning at a time when a value greater than 0 is set as the rotation speed of the compressor 4, and then drives the compressor 4 at the rotation speed set to the optimal rotation speed of the compressor. Alternatively, in a case where there is a difference between the optimal indoor temperature and the actual room temperature, the control unit 14 may drive the compressor 4 at a rotation speed obtained by correcting the optimal rotation speed of the compressor by deviation feedback control using the difference.

[0052] The order of steps S14 and subsequent steps in the flowchart of FIG. 5 is an example. For example, the steps S16, S14, S15, and S17 may be performed in this order, or the steps S14 and S15 and the steps S16 and S17 may be performed in parallel. In step S13, the outside air temperature at the time of prediction is always used as the outside air temperature, but in a case where the change in the outside air temperature is predicted, the predicted value of the outside air temperature for each predetermined time until N minutes later may be acquired, or the change in the outside air temperature for each predetermined time until N minutes later may be predicted, and the predicted value of the outside air temperature corresponding to the time of predicting the indoor temperature may be input to the room temperature prediction model 131 to predict the future indoor temperature. The room temperature prediction model 131 may be created by learning the time-series data of the indoor temperature, the outside air temperature, the rotation speed of the compressor 4, the humidity, and the solar radiation amount, and in this case, in steps S13 and S14, for example, the processing may be performed by using the measured values of a humidity sensor and a pyranometer (not shown) provided in the room, in addition to the outside air temperature measured by the outside air temperature sensor 2 and the indoor temperature measured by the indoor temperature sensor 3.(Effects)

[0053] As described above, according to the present embodiment, the target temperature can be achieved with low power consumption by the specified time in the on-timer operation. More specifically, the time-series air conditioning capacity (rotation speed of the compressor 4) that can achieve both the minimization of the power consumption and the achievement of the target temperature at the specified time while predicting the change in the room temperature based on the room temperature prediction model 131 is calculated in consideration of the indoor temperature, the outside air temperature, and the like at the time of setting the on-timer operation, and the operation start time is calculated by reverse calculation from the calculated air conditioning capacity. Then, the air conditioner 1 is operated based on the calculated time-series air conditioning capacity after the operation start time. As a result, the operation start time and the time-series air conditioning capacity corresponding to disturbances such as the change in the target temperature or the outside air temperature can be calculated, so that the target temperature can be reliably achieved with low power consumption by the specified time.

[0054] FIG. 6 is a diagram showing an example of a hardware configuration of the air conditioning system according to the embodiment.

[0055] A computer 900 includes a CPU 901, a main storage device 902, an auxiliary storage device 903, an input / output interface 904, and a communication interface 905. The control device 10, the server 20, and the user terminal 30 described above are implemented in the computer 900. Each of the functions mentioned above is stored in the auxiliary storage device 903 in the form of a program. The CPU 901 reads the program from the auxiliary storage device 903, loads the program into the main storage device 902, and executes the above-described processing in accordance with the program. The CPU 901 secures a storage area in the main storage device 902 in accordance with the program. The CPU 901 secures a storage area for storing data being processed in the auxiliary storage device 903 in accordance with the program.

[0056] A program for implementing all or some of the functions of the control device 10, the server 20, and the user terminal 30 may be recorded on a computer-readable recording medium, and the processing by each functional unit may be performed by reading the program recorded on the recording medium into a computer system and executing the program. The term "computer system" as used herein includes an OS and hardware such as peripheral devices. The term "computer system" also includes a homepage providing environment (or a display environment) in a case where a WWW system is used. The term "computer-readable recording medium" refers to portable media such as a CD, a DVD, or a USB, or a storage device such as a hard disk built into the computer system. In a case where the program is distributed to the computer 900 via a communication line, the computer 900 that receives the distribution may load the program into the main storage device 902 and execute the above-described processing. The above-described program may be for implementing only a part of the above-mentioned functions, or may also be capable of implementing the above-mentioned functions in combination with a program already recorded in the computer system.

[0057] As described above, several embodiments according to the present disclosure have been described, but all of these embodiments are presented by way of example and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, replacements, and changes can be made within the scope of the invention that does not depart from its gist. These embodiments and modifications thereof are included within the scope and the gist of the invention and are also included within the scope of the invention described in the claims and equivalents thereof.

[0058] The control device 10 and / or the server 20 is an example of a control system.

[0059] The past operation data of the air conditioner 1 is an example of actual data.

[0060] The expression (1) and the expression (1') are examples of a linear expression.<Additional Notes>

[0061] The control system, the air conditioning system, the control method, and the program according to each embodiment are understood as follows, for example.

[0062] (1) According to a first aspect, a control system for controlling an air conditioner includes a setting receiving unit that receives a setting of a target temperature and a specified time at which the target temperature is to be achieved, an optimal operation calculation unit that calculates time-series air conditioning capacity of the air conditioner such that power consumption of the air conditioner for achieving the target temperature at the specified time is minimized, and a control unit that operates the air conditioner based on the time-series air conditioning capacity.

[0063] In this manner, the target temperature can be achieved by the set time with low power consumption.

[0064] (2) According to a second aspect, the control system according to (1) further includes a room temperature prediction model that predicts an indoor temperature in a next control step following a certain control step based on an indoor temperature, an outside air temperature, and the air conditioning capacity in the certain control step, and the optimal operation calculation unit searches for a time-series combination of the indoor temperature, the outside air temperature, and the air conditioning capacity such that the power consumption for achieving the target temperature at the specified time is minimized, by using the room temperature prediction model.

[0065] As a result, the time-series air conditioning capacity such that the target temperature can be achieved by the set time with low power consumption can be calculated.

[0066] (3) According to a third aspect, in the control system according to (1) to (2), the optimal operation calculation unit searches for the combination by solving a linear programming problem in which minimizing the power consumption is set as an objective function and achieving the target temperature at the specified time is set as a constraint.

[0067] As a result, the time-series air conditioning capacity such that the target temperature can be achieved by the set time with low power consumption can be calculated.

[0068] (4) According to a fourth aspect, the control system according to (1) to (3) further includes a room temperature prediction model creation unit that creates the room temperature prediction model, which is a linear expression representing a relationship among the indoor temperature, the outside air temperature, and the air conditioning capacity in the certain control step, and the indoor temperature in the next control step, by calculating coefficients of the linear expression such that a difference between the indoor temperature predicted by the linear expression using actual data of the indoor temperature, the outside air temperature, and the air conditioning capacity, and the indoor temperature included in the actual data is minimized.

[0069] As a result, the room temperature prediction model can be created.

[0070] (5) According to a fifth aspect, in the control system according to (1) to (4), the optimal operation calculation unit predicts a transition of the indoor temperature corresponding to the time-series air conditioning capacity based on the time-series air conditioning capacity and the room temperature prediction model, and outputs the predicted transition of the indoor temperature.

[0071] As a result, the user can be provided with the prediction of the transition of the indoor temperature in a case where the on-timer operation is set. The user can check that the target temperature is achieved by the specified time by referring to the prediction of the transition of the indoor temperature.

[0072] (6) According to a sixth aspect, an air conditioning system includes an air conditioner 1 and the control system according to any one of (1) to (5). (7) According to a seventh aspect, a control method of an air conditioner includes a step of receiving a setting of a target temperature and a specified time at which the target temperature is to be achieved, a step of calculating time-series air conditioning capacity of the air conditioner such that power consumption of the air conditioner for achieving the target temperature at the specified time is minimized, and a step of operating the air conditioner based on the time-series air conditioning capacity. (8) According to an eighth aspect, a program causes a computer to execute a step of receiving a setting of a target temperature and a specified time at which the target temperature is to be achieved, a step of calculating time-series air conditioning capacity of the air conditioner such that power consumption of the air conditioner for achieving the target temperature at the specified time is minimized, and a step of operating the air conditioner based on the time-series air conditioning capacity. Industrial Applicability

[0073] According to the control system, the air conditioning system, the control method, and the program described above, the target temperature can be achieved with low power consumption by the specified time.Reference Signs List

[0074] 100: air conditioning system 1: air conditioner 2: outside air temperature sensor 3: indoor temperature sensor 4: compressor 10: control device 11: sensor information acquisition unit 12: setting receiving unit 13: optimal operation calculation unit 131: room temperature prediction model 132: optimal air conditioning capacity calculation unit 133: optimal indoor temperature calculation unit 134: optimal rotation speed calculation unit 14: control unit 15: communication unit 20: server 21: room temperature prediction model creation unit 22: communication unit 30: user terminal 900: computer 901: CPU 902: main storage device 903: auxiliary storage device 904: input / output interface 905: communication interface

Examples

Embodiment Construction

[0012]Hereinafter, a control method of an on-timer operation according to the embodiment of the present disclosure will be described with reference to FIGS. 1 to 6.

(Configuration of Air Conditioning System)

[0013]FIG. 1 is a diagram showing an example of an air conditioning system according to an embodiment. As shown in FIG. 1, an air conditioning system 100 includes an air conditioner 1, a server 20, and a user terminal 30. The air conditioner 1 includes an outside air temperature sensor 2, an indoor temperature sensor 3, a compressor 4, and a control device 10. For example, the outside air temperature sensor 2 is provided in an outdoor unit (not shown), and the indoor temperature sensor 3 is provided in an indoor unit (not shown), but the installation locations of the outside air temperature sensor 2 and the indoor temperature sensor 3 are not limited thereto. The outside air temperature sensor 2 and the indoor temperature sensor 3 are connected to the control device 10, and the co...

Technical Field

[0001] The present disclosure relates to a control system, an air conditioning system, a control method, and a program. The present disclosure claims priority based on Japanese Patent Application No. 2023-131587, filed in Japan on August 10, 2023, the content of which is incorporated herein by reference.Background Art

[0002] A function called an on-timer operation is provided, in which the air conditioner is automatically started before a specified time designated by a user, and cooling operation or heating operation is performed such that a room temperature reaches a target temperature by the specified time. By using the on-timer operation, for example, the user can designate a return time as the specified time, and the air conditioning of the house can be performed to a desired target temperature at the time of returning home. PTL 1 discloses an air conditioning system that generates a building load prediction model by learning an indoor temperature, an outside air temperature, and an air conditioning capacity exhibited by an air conditioner, inputs a predicted value of the indoor temperature, the air conditioning capacity, and the outside air temperature at the specified time at the time of determining an air conditioning start time to the building load prediction model to predict a building load, determines a pre-operation start time in 5-minute increments in a range of 0 to 40 minutes before the specified time according to the predicted building load, and starts the operation at the determined pre-operation start time. According to the air conditioning system of PTL 1, for a room having a large building load, the air conditioning can be automatically started earlier than for a room having a small building load, so that the possibility that the temperature of the room does not reach the target temperature by the specified time even in a case where the on-timer operation is performed in a case where the building load is large can be reduced. However, even in a case where the target temperature can be achieved by this control, for example, the air conditioning may be started earlier than necessary, which may increase the power consumption.Citation ListPatent Literature

[0003] [PTL 1] Japanese Unexamined Patent Application Publication No. 2020-125868Summary of InventionTechnical Problem

[0004] In the on-timer operation, a control method that can achieve both comfort and low power consumption is required.

[0005] The present disclosure provides a control system, an air conditioning system, a control method, and a program that can solve the above-described problems.Solution to Problem

[0006] According to an aspect of the present disclosure, a control system for controlling an air conditioner includes a setting receiving unit that receives a setting of a target temperature and a specified time at which the target temperature is to be achieved, an optimal operation calculation unit that calculates time-series air conditioning capacity of the air conditioner such that power consumption of the air conditioner for achieving the target temperature at the specified time is minimized, and a control unit that operates the air conditioner based on the time-series air conditioning capacity.

[0007] According to another aspect of the present disclosure, an air conditioning system includes an air conditioner and the control system.

[0008] According to still another aspect of the present disclosure, a control method of an air conditioner includes a step of receiving a setting of a target temperature and a specified time at which the target temperature is to be achieved, a step of calculating time-series air conditioning capacity of the air conditioner such that power consumption of the air conditioner for achieving the target temperature at the specified time is minimized, and a step of operating the air conditioner based on the time-series air conditioning capacity.

[0009] According to still another aspect of the present disclosure, a program causing a computer to execute a step of receiving a setting of a target temperature and a specified time at which the target temperature is to be achieved, a step of calculating time-series air conditioning capacity of the air conditioner such that power consumption of the air conditioner for achieving the target temperature at the specified time is minimized, and a step of operating the air conditioner based on the time-series air conditioning capacity.Advantageous Effects of Invention

[0010] According to the control system, the air conditioning system, the control method, and the program described above, the target temperature can be achieved with low power consumption by the specified time.Brief Description of Drawings

[0011] FIG. 1 is a diagram showing an example of an air conditioning system according to an embodiment. FIG. 2 is a diagram showing an example of a room temperature prediction model according to the embodiment. FIG. 3 is a block diagram showing a detailed configuration example of an optimal operation calculation unit according to the embodiment. FIG. 4A is a first diagram for describing a method of calculating an optimal air conditioning capacity according to the embodiment. FIG. 4B is a second diagram for describing the method of calculating the optimal air conditioning capacity according to the embodiment. FIG. 5 is a flowchart showing an example of control of an on-timer operation according to the embodiment. FIG. 6 is a diagram showing an example of a hardware configuration of the air conditioning system in the embodiment. Description of Embodiments<Embodiment>

[0012] Hereinafter, a control method of an on-timer operation according to the embodiment of the present disclosure will be described with reference to FIGS. 1 to 6.(Configuration of Air Conditioning System)

[0013] FIG. 1 is a diagram showing an example of an air conditioning system according to an embodiment. As shown in FIG. 1, an air conditioning system 100 includes an air conditioner 1, a server 20, and a user terminal 30. The air conditioner 1 includes an outside air temperature sensor 2, an indoor temperature sensor 3, a compressor 4, and a control device 10. For example, the outside air temperature sensor 2 is provided in an outdoor unit (not shown), and the indoor temperature sensor 3 is provided in an indoor unit (not shown), but the installation locations of the outside air temperature sensor 2 and the indoor temperature sensor 3 are not limited thereto. The outside air temperature sensor 2 and the indoor temperature sensor 3 are connected to the control device 10, and the control device 10 acquires temperatures measured by the outside air temperature sensor 2 and the indoor temperature sensor 3. The compressor 4 and the control device 10 are connected to each other, and the control device 10 controls the compressor 4 and detects an operation state of the compressor 4. For example, the control device 10 can operate the compressor 4 at a desired rotation speed and can detect the rotation speed thereof. The server 20 creates a room temperature prediction model used to calculate an air conditioning start time of the on-timer operation. The user terminal 30 is a smartphone or the like owned by a user of the air conditioner 1, and the user can perform a setting of the target temperature and the specified time in the on-timer operation, an execution instruction of the on-timer operation, and the like from the user terminal 30. The control device 10, the server 20, and the user terminal 30 are communicably connected to each other via a network NW.(Configuration of Control Device)

[0014] The control device 10 includes a sensor information acquisition unit 11, a setting receiving unit 12, an optimal operation calculation unit 13, a control unit 14, and a communication unit 15.

[0015] The sensor information acquisition unit 11 acquires an outside air temperature measured by the outside air temperature sensor 2 and an indoor temperature measured by the indoor temperature sensor 3.

[0016] The setting receiving unit 12 receives settings of a target temperature of an air conditioning target space and a specified time at which the target temperature is to be achieved, and the like. For example, the target temperature and the specified time are set by using a remote controller (not shown) or the user terminal 30.

[0017] The optimal operation calculation unit 13 calculates a time (referred to as an arrival time) until the indoor temperature of the air conditioning target space reaches the target temperature and an air conditioning capacity required at that time. The air conditioning capacity is a strength of heating or cooling exhibited by the air conditioner 1. The air conditioning capacity has a positive correlation with power used for air conditioning by the air conditioner 1, and can be calculated from, for example, a rotation speed of the compressor 4. The optimal operation calculation unit 13 calculates a transition of time-series air conditioning capacity such that the target temperature can be achieved by the specified time with the lowest power consumption based on a room temperature prediction model 131 created by a room temperature prediction model creation unit 21 described below and the outside air temperature, the indoor temperature, and the like measured by the air conditioner 1, and calculates the arrival time from the result. The optimal operation calculation unit 13 converts the time-series air conditioning capacity into a rotation speed of the compressor 4 to calculate a time-series rotation speed of the compressor 4 for achieving the target temperature by the specified time with the lowest power consumption. Further, the optimal operation calculation unit 13 predicts a transition of time-series indoor temperature in a case where the target temperature can be achieved by the specified time with the lowest power consumption, and provides the user with the prediction of the indoor temperature transition during the on-timer operation by transmitting the prediction to the user terminal 30.

[0018] The control unit 14 controls the compressor 4 and the like to execute air conditioning. During the on-timer operation, the control unit 14 starts the operation of the compressor 4 and the like an arrival time before the specified time set by the user, which is calculated by the optimal operation calculation unit 13, operates the compressor 4 according to the time-series rotation speed of the compressor 4 calculated by the optimal operation calculation unit 13, and performs cooling operation or heating operation.

[0019] The communication unit 15 communicates with the server 20 and the user terminal 30. For example, as learning data required for creating the room temperature prediction model 131, the communication unit 15 transmits the outside air temperature and the indoor temperature which are acquired by the sensor information acquisition unit 11, the rotation speed of the compressor 4 which is detected by the control unit 14, and the specified time and the target temperature which are acquired by the setting receiving unit 12, to the server 20. The communication unit 15 acquires the room temperature prediction model 131 and the like from the server 20. The communication unit 15 acquires the target temperature, the specified time, and the like transmitted from the user terminal 30.(Configuration of Server)

[0020] The server 20 includes the room temperature prediction model creation unit 21 and a communication unit 22.

[0021] The room temperature prediction model creation unit 21 creates the room temperature prediction model 131 for predicting the arrival time required to set the indoor temperature of the air conditioning target space to the target temperature. The room temperature prediction model 131 creates a prediction model that receives the indoor temperature (K), the outside air temperature (K), and the air conditioning capacity (W / m 2< ) and outputs a future indoor temperature. FIG. 2 shows an example of the room temperature prediction model 131.(Room Temperature Prediction Model)

[0022] An Auto-Regressive with eXogenous model (ARX model) shown in FIG. 2 is a linear multiple regression model showing a relationship among an indoor temperature T in (k) at a certain control step k, a deviation T O-in (k) obtained by subtracting the indoor temperature T in (k) from an outside air temperature To(k), and an air conditioning capacity φ h (k). When the ARX model of FIG. 2 is arranged, the following expression (1) is obtained.

[0023] The room temperature prediction model creation unit 21 calculates coefficients a 1 , a 2 , ..., a m , b 11 , b 12 , ..., b 1m , b 21 , b 22 , ..., b 2m of the expression (1), a bias term w 0 , which is a constant representing noise or disturbance, and a step length m that can maintain a high prediction accuracy, using past operation data of the air conditioner 1, that is, the outside air temperature measured by the outside air temperature sensor 2, the indoor temperature measured by the indoor temperature sensor 3, and the rotation speed of the compressor 4 instructed by the control unit 14, which are collected at a predetermined cycle in a past predetermined period. The rotation speed of the compressor 4 can be converted into an air conditioning capacity (W / m 2< ) by the following expressions (2) to (4).

[0024] During heating operation, when the outside air temperature T O is in the frost-free temperature region (T O ≤ -7°C or 5.5°C < T O ) φ h T O = φ − 7 + φ 7 − φ − 7 ÷ 7 − − 7 × T O − − 7

[0025] During heating operation, when the outside air temperature T O is in the frost temperature region (-7°C < T O ≤ 5.5°C) φ h T O = φ − 7 + φ 2 − φ − 7 ÷ 2 − − 7 × T O − − 7

[0026] Here, φ(-7), φ(2), and φ(7) are air conditioning capacities at outside air temperatures of -7°C, 2°C, and 7°C, respectively.

[0027] In case of cooling operation φ h T O = φ 35 + φ 29 − φ 35 ÷ 35 − 29 × 35 − T O

[0028] Here, φ(35) and φ(29) are air conditioning capacities at outside air temperatures of 35°C and 29°C, respectively.

[0029] In a case where the rotation speed of the compressor 4 is ncmp and K1, K2, K3, K4, and K5 are predetermined constants, the relationship between ncmp and φ(-7), φ(2), φ(7), φ(29), and φ(35) is as follows.

[0030] The room temperature prediction model creation unit 21 converts the rotation speed of the compressor 4 into φ(-7), φ(2), φ(7), φ(29), and φ(35) by the expression (4), and converts the rotation speed of the compressor 4 into the air conditioning capacity φ h (T O ) by using any of the expression (2), the expression (2'), and the expression (3) according to the outside air temperature T O .

[0031] For example, the room temperature prediction model creation unit 21 may calculate the coefficients a 1 , and the like by a least-squares method so as to minimize a square of a difference (RMSE: Root Mean Squared Error) between a measured value of an actual indoor temperature included in the operation data of the air conditioner 1 and a predicted value of the indoor temperature obtained by substituting the measured value of the actual indoor temperature, a measured value of the outside air temperature, and an air conditioning capacity calculated from the rotation speed of the compressor 4 included in the operation data into the expression (1). Alternatively, in a case where appropriate values of the coefficients a 1 , and the like cannot be calculated by the least-squares method due to multicollinearity between explanatory variables or in a case where overfitting occurs, the coefficients a 1 , and the like may be calculated by ridge regression. In a case where a matrix of input data is X, a matrix of output data is Y, and a matrix of coefficients is W, the least-squares method obtains the coefficients W by W = (X T< X) -1< X T< Y, but the ridge regression obtains the coefficients W by W = (X T< X - dI) -1< X T< Y using a unit matrix I. In a case where the coefficients a 1 , and the like are calculated by the ridge regression, the room temperature prediction model creation unit 21 appropriately sets a parameter d of the ridge regression in addition to the step length m to calculate the coefficients a 1 , and the like. For example, various values may be set for m and d, the coefficients a 1 , and the like may be calculated for each combination of m and d, and m and d with the minimum RMSE may be adopted from among the calculated coefficients. A method of calculating the coefficients a 1 , and the like is not limited to the above, and any other method can be used. It is preferable to use the operation data of the air conditioner 1 installed in the actual air conditioning target space as the time-series data of the indoor temperature, the outside air temperature, and the rotation speed of the compressor 4 used as the learning data, but the present disclosure is not limited thereto. For example, the operation data of another air conditioner having the same capacity as the air conditioner 1 provided in a space having the same property as the air conditioning target space may be used. In a case where the coefficients a 1 , and the like are calculated, the room temperature prediction model creation unit 21 applies the calculated coefficients a 1 , and the like to the expression (1) to create the room temperature prediction model 131.

[0032] The communication unit 22 communicates with the control device 10 and the like. For example, the communication unit 22 receives the indoor temperature, the outside air temperature, the rotation speed of the compressor 4, and the like from the control device 10, and outputs these values to the room temperature prediction model creation unit 21. The room temperature prediction model creation unit 21 stores and accumulates these data as the learning data for calculating the coefficients a 1 , and the like. The communication unit 22 transmits the room temperature prediction model 131 created by the room temperature prediction model creation unit 21 to the control device 10.

[0033] The user terminal 30 is a portable terminal such as a smartphone owned by the user of the air conditioner 1. The user operates the user terminal 30 to set the target temperature or the specified time and to issue an instruction to perform the on-timer operation. Then, the user terminal 30 transmits the setting information and the instruction information to the control device 10 of the air conditioner 1.

[0034] The configuration illustrated in FIG. 1 is an example. For example, the optimal operation calculation unit 13 may be provided in the server 20 to perform processing with a large amount of calculation by the server 20, such as transmitting the calculation result to the control device 10, or the room temperature prediction model creation unit 21 may be provided in the control device 10. The room temperature prediction model creation unit 21 may receive information on the humidity and the solar radiation amount, and create the room temperature prediction model 131 by learning the time-series data of the indoor temperature, the outside air temperature, the rotation speed of the compressor 4, the humidity, and the solar radiation amount.(Details of Optimal Operation Calculation)

[0035] FIG. 3 shows a detailed configuration example of the optimal operation calculation unit 13. As shown in the drawing, the optimal operation calculation unit 13 includes an optimal air conditioning capacity calculation unit 132, an optimal indoor temperature calculation unit 133, and an optimal rotation speed calculation unit 134. The optimal air conditioning capacity calculation unit 132 has a solver that solves a linear programming problem or the room temperature prediction model 131, receives upper and lower limit values of the air conditioning capacity, the outside air temperature, the indoor temperature, the target temperature, and a time (time until the on-timer operation) until the specified time as input data, analyzes which air conditioning operation can achieve the target temperature with the lowest power consumption by the specified time, and calculates the time-series air conditioning capacity (power consumption per unit time) and the arrival time in this case. The functions of the optimal air conditioning capacity calculation unit 132 will be specifically described with reference to FIGS. 4A and 4B.

[0036] For example, it is assumed that m = 1 is obtained as the step length having a high prediction accuracy of the indoor temperature. In this case, when the expression (1) is arranged, the following expression (1') is obtained. T in k + 1 = a 1 T in k + b 11 φ h k + b 21 T O k + w 0

[0037] The coefficients a 1 , and the like of the expression (1') are not exactly the same as the coefficients a 1 , and the like of the expression (1), and for example, in a case of the coefficient a 1 , the expression (1) is replaced with To - T in for T o-in , arranged, and then replaced with, for example, (a 1 - b 21 ) as a 1 . In the expression (1'), T in is the indoor temperature, φ h is the heating capacity, T O is the outside air temperature, and w O is the bias term. The expression (1') is an example of the room temperature prediction model 131 included in the optimal air conditioning capacity calculation unit 132. In a case where the heating capacity φ h and the outdoor temperature T O are given until N - 1 minutes later, the room temperature T in until N minutes later can be represented by an expression (5) of FIG. 4A.

[0038] The optimal air conditioning capacity calculation unit 132 calculates an optimal heating capacity φ h that satisfies upper and lower limit values of the heating capacity and the target temperature T min and minimizes a total of the heating capacity until the target temperature T min is achieved by solving a linear programming problem (expression (6)) shown in FIG. 4B using the expression (5). The expression (6) is an expression in a case where the heating operation is performed by the on-timer operation and the target temperature is achieved by the specified time, as an example, and a linear programming problem can be formulated in the same manner in a case of the cooling operation. In the expression (6), c represents a 1 × N matrix in which all elements are 1, φ min represents a lower limit value of the heating capacity, and φ max represents an upper limit value of the heating capacity. φ min and φ max are optionally set by a designer or the like. "minimize" represents that an objective function c T< φ h is minimized (the heating capacity is minimized), and "subject to" represents a constraint. The first constraint from the top is a constraint that the heating capacity is equal to or greater than the lower limit value φ min , the second constraint is a constraint that the heating capacity is equal to or smaller than the upper limit value φ max , and the third constraint, using expression (5), is a constraint that the future indoor temperature is equal to or greater than T min (in a case of cooling, it is set to be equal to or smaller than T min ). For example, in a case where the target temperature is T SP (°C) and the indoor temperature reaches T SP (°C) after M (<N) minutes (M minutes is the target time), the room temperature lower limit T min that the future indoor temperature is to satisfy is set as follows. T min = 0 , … , 273.15 + T sp , … , 273.15 + T sp T

[0039] Here, in a case where the length of one control step is set to, for example, 1 minute, the first 0 of the matrix T min indicates the room temperature lower limit to be satisfied after 1 minute, and in this example, M zeros are arranged from the beginning. Then, 273.15 + T sp (K) is set in the (M + 1)-th to N-th elements. By setting in this way and solving the linear programming problem of the expression (6), the heating capacity per minute in a case where the indoor temperature T sp (°C) is achieved after M minutes and the power consumption is minimized can be calculated. For example, the optimal operation calculation unit 13 uses the indoor temperature measured by the indoor temperature sensor 3 at the time of prediction (at the time of starting to solve the linear programming problem) as an initial value T in (0) of the indoor temperature, uses 0 as an initial value φ h (0) of the heating capacity, uses the outside air temperature measured by the outside air temperature sensor 2 at the time of prediction as an initial value T O (0) of the outside air temperature, predicts the indoor temperature after 1 minute by the expression (1'), sets any value to the heating capacity φ h (1) after 1 minute, uses the indoor temperature after 1 minute predicted by the expression (1') as the indoor temperature T in (1), uses the outside air temperature at the time of prediction as the indoor temperature T O (1) after 1 minute as it is, predicts the indoor temperature after 2 minutes by the expression (1'), and repeats the same calculation for the subsequent time to search for a time-series combination of indoor temperature T in , outside air temperature T O , and heating capacity φ h satisfying the expression (6). As a method of efficiently searching for a time-series combination of T in , To, and φ h satisfying the expression (6), a simplex method, an interior point method, and the like are known. The optimal operation calculation unit 13 solves the linear programming problem of FIG. 4B by using, for example, the simplex method or the interior point method. In a case where the linear programming problem is solved, for example, the heating capacity per minute from the time of prediction to N minutes later is obtained. φ h = 0 , 0 , 0 , φ h 1 , φ h 2 , φ h 3 , …

[0040] For example, it is assumed that a calculation result such as the expression (7) is obtained. A time slot in which the heating capacity is 0 is a time slot in which the operation is not performed, and a time corresponding to the control step in which a value greater than 0 is set is the operation start time in the on-timer operation. In a case of the expression (7), it is shown that the air conditioner 1 is stopped until 2 minutes later (the first 0 indicates that the heating capacity is 0 after 0 minutes, the second 0 indicates that the heating capacity is 0 after 1 minute, and the third 0 indicates that the heating capacity is 0 after 2 minutes), the operation of the air conditioner 1 is started at the heating capacity φ h1 after 3 minutes, the operation is performed at the heating capacity φ h2 after 4 minutes, the operation is performed at the heating capacity φ h3 after 5 minutes, and the like, and the indoor temperature T sp (°C) is achieved after M minutes while minimizing the power consumption. The optimal operation calculation unit 13 solves the linear programming problem illustrated in the expression (6) to calculate the time-series air conditioning capacity (for example, the expression (7)), and outputs this data to the optimal indoor temperature calculation unit 133 and the optimal rotation speed calculation unit 134. The time-series air conditioning capacity calculated by the optimal operation calculation unit 13 is referred to as the optimal air conditioning capacity.

[0041] The optimal indoor temperature calculation unit 133 has the room temperature prediction model 131. In a case where the optimal air conditioning capacity is input, the optimal indoor temperature calculation unit 133 inputs the optimal air conditioning capacity, the outside air temperature at the time of prediction, and the indoor temperature at the time of prediction to the room temperature prediction model 131 (the indoor temperature at the time of prediction is input as the initial value of the indoor temperature, and the outside air temperature is input as the outside air temperature at each time after the time of prediction), and predicts the indoor temperature for each control step until M minutes later (or until N minutes later) by the room temperature prediction model 131. As a result, for example, the transition of the indoor temperature per minute from the current time (time of prediction) to the specified time is predicted. The time-series indoor temperature predicted in this way is referred to as the optimal indoor temperature. The optimal indoor temperature calculation unit 133 transmits the optimal indoor temperature to the user terminal 30 through the communication unit 15. The user terminal 30 acquires the optimal indoor temperature and displays the optimal indoor temperature on a display unit. As a result, the user can check the prediction of the transition of the indoor temperature for the on-timer operation instructed by the user.

[0042] In a case where the optimal air conditioning capacity is input, the optimal rotation speed calculation unit 134 converts the optimal air conditioning capacity into a time-series rotation speed of the compressor 4 (referred to as an optimal rotation speed of the compressor), and outputs the converted rotation speed to the control unit 14. The optimal rotation speed calculation unit 134 calculates the rotation speed of the compressor 4 by reverse calculation from the air conditioning capacity by using the expressions (2) to (4), and converts the time-series air conditioning capacity into the time-series rotation speed of the compressor 4. In a case where the on-timer operation is set, the control unit 14 controls the compressor 4 based on the optimal rotation speed of the compressor (for example, the expression (7)) acquired from the optimal rotation speed calculation unit 134. The control unit 14 may control the compressor 4 as the optimal rotation speed of the compressor, or may correct the optimal rotation speed of the compressor by deviation feedback control (for example, PID control or PI control) such that a difference between the optimal indoor temperature and the actual indoor temperature is close to 0, and then control the compressor 4 by using the corrected rotation speed.(Operation)

[0043] Next, an operation of the air conditioning system 100 according to the present embodiment will be described with reference to FIG. 5.

[0044] FIG. 5 is a flowchart showing an example of control of an on-timer operation according to the embodiment.

[0045] First, the room temperature prediction model creation unit 21 creates the room temperature prediction model 131 (step S11). The room temperature prediction model creation unit 21 creates the room temperature prediction model 131 based on the past operation data of the air conditioner 1, for example, the time-series of indoor temperature, outside air temperature, and rotation speed of the compressor 4, and the ARX model illustrated in FIG. 2. The room temperature prediction model creation unit 21 transmits the created room temperature prediction model 131 to the control device 10 through the communication unit 22. In the control device 10, the optimal operation calculation unit 13 acquires and stores the transmitted room temperature prediction model 131.

[0046] Next, the user sets the operation mode (cooling operation or heating operation), the target temperature, and the specified time to the control device 10 by using the user terminal 30, a remote controller (not shown), or the like, and issues an instruction to perform the on-timer operation (step S12). The setting receiving unit 12 acquires the operation mode, the target temperature, the specified time, and the instruction to execute the on-timer operation through the communication unit 15, and outputs these pieces of information to the optimal operation calculation unit 13.

[0047] Next, the optimal operation calculation unit 13 calculates the optimal air conditioning capacity by using the optimal air conditioning capacity calculation unit 132 (step S13). The optimal air conditioning capacity calculation unit 132 acquires the outside air temperature measured by the outside air temperature sensor 2, the indoor temperature measured by the indoor temperature sensor 3, the target temperature and the specified time set by the user, and the upper and lower limit values of the air conditioning capacity, and calculates the optimal air conditioning capacity by solving the linear programming problem as illustrated in FIG. 4B. The upper and lower limit values of the air conditioning capacity are set in advance, and the optimal operation calculation unit 13 stores these values. The optimal air conditioning capacity calculation unit 132 outputs the optimal air conditioning capacity to the optimal indoor temperature calculation unit 133 and the optimal rotation speed calculation unit 134.

[0048] Next, the optimal operation calculation unit 13 calculates the optimal indoor temperature by using the optimal indoor temperature calculation unit 133 (step S14). The optimal indoor temperature calculation unit 133 inputs the outside air temperature measured by the outside air temperature sensor 2, the indoor temperature measured by the indoor temperature sensor 3, and the initial value of the air conditioning capacity to the room temperature prediction model 131 (for example, the expression (1')), and predicts the indoor temperature after one control step. The optimal indoor temperature calculation unit 133 inputs the outside air temperature measured by the outside air temperature sensor 2, the predicted value of the indoor temperature after one control step, and the air conditioning capacity after one control step based on the optimal air conditioning capacity to the expression (1'), and predicts the indoor temperature after two control steps. For three or more control steps, the optimal indoor temperature calculation unit 133 also inputs the predicted indoor temperature and the air conditioning capacity designated by the optimal air conditioning capacity to the room temperature prediction model 131 to sequentially predict the future indoor temperature for each control step.

[0049] Next, the optimal operation calculation unit 13 notifies the user of the optimal indoor temperature (step S15). The optimal operation calculation unit 13 transmits the optimal indoor temperature calculated by the optimal indoor temperature calculation unit 133 to the user terminal 30 through the communication unit 15. The user terminal 30 receives the optimal indoor temperature and outputs the received optimal indoor temperature to the display unit. As a result, the user can understand how the indoor temperature transitions to the target temperature by the on-timer operation. The optimal indoor temperature may be transmitted to the remote controller (not shown), and the display unit of the remote controller may display the prediction of the transition of the indoor temperature.

[0050] Next, the optimal operation calculation unit 13 calculates the optimal rotation speed of the compressor by using the optimal rotation speed calculation unit 134 (step S16). The optimal rotation speed calculation unit 134 converts the optimal air conditioning capacity acquired from the optimal air conditioning capacity calculation unit 132 into the rotation speed of the compressor 4 by using the expressions (2) to (4) to calculate the optimal rotation speed of the compressor. The optimal operation calculation unit 13 outputs the optimal rotation speed of the compressor to the control unit 14.

[0051] Next, the control unit 14 starts the air conditioning (step S17). The control unit 14 controls a refrigerant circuit (not shown) such that the air conditioning can be performed in the operation mode designated in the on-timer operation, and starts the air conditioning based on the optimal rotation speed of the compressor. The optimal rotation speed of the compressor is set to, for example, the rotation speed of the compressor 4 per minute from the current time (time of prediction) to N minutes later. The control unit 14 starts the air conditioning at a time when a value greater than 0 is set as the rotation speed of the compressor 4, and then drives the compressor 4 at the rotation speed set to the optimal rotation speed of the compressor. Alternatively, in a case where there is a difference between the optimal indoor temperature and the actual room temperature, the control unit 14 may drive the compressor 4 at a rotation speed obtained by correcting the optimal rotation speed of the compressor by deviation feedback control using the difference.

[0052] The order of steps S14 and subsequent steps in the flowchart of FIG. 5 is an example. For example, the steps S16, S14, S15, and S17 may be performed in this order, or the steps S14 and S15 and the steps S16 and S17 may be performed in parallel. In step S13, the outside air temperature at the time of prediction is always used as the outside air temperature, but in a case where the change in the outside air temperature is predicted, the predicted value of the outside air temperature for each predetermined time until N minutes later may be acquired, or the change in the outside air temperature for each predetermined time until N minutes later may be predicted, and the predicted value of the outside air temperature corresponding to the time of predicting the indoor temperature may be input to the room temperature prediction model 131 to predict the future indoor temperature. The room temperature prediction model 131 may be created by learning the time-series data of the indoor temperature, the outside air temperature, the rotation speed of the compressor 4, the humidity, and the solar radiation amount, and in this case, in steps S13 and S14, for example, the processing may be performed by using the measured values of a humidity sensor and a pyranometer (not shown) provided in the room, in addition to the outside air temperature measured by the outside air temperature sensor 2 and the indoor temperature measured by the indoor temperature sensor 3.(Effects)

[0053] As described above, according to the present embodiment, the target temperature can be achieved with low power consumption by the specified time in the on-timer operation. More specifically, the time-series air conditioning capacity (rotation speed of the compressor 4) that can achieve both the minimization of the power consumption and the achievement of the target temperature at the specified time while predicting the change in the room temperature based on the room temperature prediction model 131 is calculated in consideration of the indoor temperature, the outside air temperature, and the like at the time of setting the on-timer operation, and the operation start time is calculated by reverse calculation from the calculated air conditioning capacity. Then, the air conditioner 1 is operated based on the calculated time-series air conditioning capacity after the operation start time. As a result, the operation start time and the time-series air conditioning capacity corresponding to disturbances such as the change in the target temperature or the outside air temperature can be calculated, so that the target temperature can be reliably achieved with low power consumption by the specified time.

[0054] FIG. 6 is a diagram showing an example of a hardware configuration of the air conditioning system according to the embodiment.

[0055] A computer 900 includes a CPU 901, a main storage device 902, an auxiliary storage device 903, an input / output interface 904, and a communication interface 905. The control device 10, the server 20, and the user terminal 30 described above are implemented in the computer 900. Each of the functions mentioned above is stored in the auxiliary storage device 903 in the form of a program. The CPU 901 reads the program from the auxiliary storage device 903, loads the program into the main storage device 902, and executes the above-described processing in accordance with the program. The CPU 901 secures a storage area in the main storage device 902 in accordance with the program. The CPU 901 secures a storage area for storing data being processed in the auxiliary storage device 903 in accordance with the program.

[0056] A program for implementing all or some of the functions of the control device 10, the server 20, and the user terminal 30 may be recorded on a computer-readable recording medium, and the processing by each functional unit may be performed by reading the program recorded on the recording medium into a computer system and executing the program. The term "computer system" as used herein includes an OS and hardware such as peripheral devices. The term "computer system" also includes a homepage providing environment (or a display environment) in a case where a WWW system is used. The term "computer-readable recording medium" refers to portable media such as a CD, a DVD, or a USB, or a storage device such as a hard disk built into the computer system. In a case where the program is distributed to the computer 900 via a communication line, the computer 900 that receives the distribution may load the program into the main storage device 902 and execute the above-described processing. The above-described program may be for implementing only a part of the above-mentioned functions, or may also be capable of implementing the above-mentioned functions in combination with a program already recorded in the computer system.

[0057] As described above, several embodiments according to the present disclosure have been described, but all of these embodiments are presented by way of example and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, replacements, and changes can be made within the scope of the invention that does not depart from its gist. These embodiments and modifications thereof are included within the scope and the gist of the invention and are also included within the scope of the invention described in the claims and equivalents thereof.

[0058] The control device 10 and / or the server 20 is an example of a control system.

[0059] The past operation data of the air conditioner 1 is an example of actual data.

[0060] The expression (1) and the expression (1') are examples of a linear expression.<Additional Notes>

[0061] The control system, the air conditioning system, the control method, and the program according to each embodiment are understood as follows, for example.

[0062] (1) According to a first aspect, a control system for controlling an air conditioner includes a setting receiving unit that receives a setting of a target temperature and a specified time at which the target temperature is to be achieved, an optimal operation calculation unit that calculates time-series air conditioning capacity of the air conditioner such that power consumption of the air conditioner for achieving the target temperature at the specified time is minimized, and a control unit that operates the air conditioner based on the time-series air conditioning capacity.

[0063] In this manner, the target temperature can be achieved by the set time with low power consumption.

[0064] (2) According to a second aspect, the control system according to (1) further includes a room temperature prediction model that predicts an indoor temperature in a next control step following a certain control step based on an indoor temperature, an outside air temperature, and the air conditioning capacity in the certain control step, and the optimal operation calculation unit searches for a time-series combination of the indoor temperature, the outside air temperature, and the air conditioning capacity such that the power consumption for achieving the target temperature at the specified time is minimized, by using the room temperature prediction model.

[0065] As a result, the time-series air conditioning capacity such that the target temperature can be achieved by the set time with low power consumption can be calculated.

[0066] (3) According to a third aspect, in the control system according to (1) to (2), the optimal operation calculation unit searches for the combination by solving a linear programming problem in which minimizing the power consumption is set as an objective function and achieving the target temperature at the specified time is set as a constraint.

[0067] As a result, the time-series air conditioning capacity such that the target temperature can be achieved by the set time with low power consumption can be calculated.

[0068] (4) According to a fourth aspect, the control system according to (1) to (3) further includes a room temperature prediction model creation unit that creates the room temperature prediction model, which is a linear expression representing a relationship among the indoor temperature, the outside air temperature, and the air conditioning capacity in the certain control step, and the indoor temperature in the next control step, by calculating coefficients of the linear expression such that a difference between the indoor temperature predicted by the linear expression using actual data of the indoor temperature, the outside air temperature, and the air conditioning capacity, and the indoor temperature included in the actual data is minimized.

[0069] As a result, the room temperature prediction model can be created.

[0070] (5) According to a fifth aspect, in the control system according to (1) to (4), the optimal operation calculation unit predicts a transition of the indoor temperature corresponding to the time-series air conditioning capacity based on the time-series air conditioning capacity and the room temperature prediction model, and outputs the predicted transition of the indoor temperature.

[0071] As a result, the user can be provided with the prediction of the transition of the indoor temperature in a case where the on-timer operation is set. The user can check that the target temperature is achieved by the specified time by referring to the prediction of the transition of the indoor temperature.

[0072] (6) According to a sixth aspect, an air conditioning system includes an air conditioner 1 and the control system according to any one of (1) to (5). (7) According to a seventh aspect, a control method of an air conditioner includes a step of receiving a setting of a target temperature and a specified time at which the target temperature is to be achieved, a step of calculating time-series air conditioning capacity of the air conditioner such that power consumption of the air conditioner for achieving the target temperature at the specified time is minimized, and a step of operating the air conditioner based on the time-series air conditioning capacity. (8) According to an eighth aspect, a program causes a computer to execute a step of receiving a setting of a target temperature and a specified time at which the target temperature is to be achieved, a step of calculating time-series air conditioning capacity of the air conditioner such that power consumption of the air conditioner for achieving the target temperature at the specified time is minimized, and a step of operating the air conditioner based on the time-series air conditioning capacity. Industrial Applicability

[0073] According to the control system, the air conditioning system, the control method, and the program described above, the target temperature can be achieved with low power consumption by the specified time.Reference Signs List

[0074] 100: air conditioning system 1: air conditioner 2: outside air temperature sensor 3: indoor temperature sensor 4: compressor 10: control device 11: sensor information acquisition unit 12: setting receiving unit 13: optimal operation calculation unit 131: room temperature prediction model 132: optimal air conditioning capacity calculation unit 133: optimal indoor temperature calculation unit 134: optimal rotation speed calculation unit 14: control unit 15: communication unit 20: server 21: room temperature prediction model creation unit 22: communication unit 30: user terminal 900: computer 901: CPU 902: main storage device 903: auxiliary storage device 904: input / output interface 905: communication interface

Examples

Embodiment Construction

[0012]Hereinafter, a control method of an on-timer operation according to the embodiment of the present disclosure will be described with reference to FIGS. 1 to 6.

(Configuration of Air Conditioning System)

[0013]FIG. 1 is a diagram showing an example of an air conditioning system according to an embodiment. As shown in FIG. 1, an air conditioning system 100 includes an air conditioner 1, a server 20, and a user terminal 30. The air conditioner 1 includes an outside air temperature sensor 2, an indoor temperature sensor 3, a compressor 4, and a control device 10. For example, the outside air temperature sensor 2 is provided in an outdoor unit (not shown), and the indoor temperature sensor 3 is provided in an indoor unit (not shown), but the installation locations of the outside air temperature sensor 2 and the indoor temperature sensor 3 are not limited thereto. The outside air temperature sensor 2 and the indoor temperature sensor 3 are connected to the control device 10, and the co...

Claims

1. A control system for controlling an air conditioner, the control system comprising: a setting receiving unit that receives a setting of a target temperature and a specified time at which the target temperature is to be achieved; an optimal operation calculation unit that calculates time-series air conditioning capacity of the air conditioner such that power consumption of the air conditioner for achieving the target temperature at the specified time is minimized; and a control unit that operates the air conditioner based on the time-series air conditioning capacity.

2. The control system according to Claim 1, further comprising: a room temperature prediction model that predicts an indoor temperature in a next control step following a certain control step based on an indoor temperature, an outside air temperature, and the air conditioning capacity in the certain control step, wherein the optimal operation calculation unit searches for a time-series combination of the indoor temperature, the outside air temperature, and the air conditioning capacity such that the power consumption for achieving the target temperature at the specified time is minimized, by using the room temperature prediction model.

3. The control system according to Claim 2, wherein the optimal operation calculation unit searches for the combination by solving a linear programming problem in which minimizing the power consumption is set as an objective function and achieving the target temperature at the specified time is set as a constraint.

4. The control system according to Claim 2 or 3, further comprising: a room temperature prediction model creation unit that creates the room temperature prediction model, which is a linear expression representing a relationship among the indoor temperature, the outside air temperature, and the air conditioning capacity in the certain control step, and the indoor temperature in the next control step, by calculating coefficients of the linear expression such that a difference between the indoor temperature predicted by the linear expression using actual data of the indoor temperature, the outside air temperature, and the air conditioning capacity, and the indoor temperature included in the actual data is minimized.

5. The control system according to Claim 2 or 3, wherein the optimal operation calculation unit predicts a transition of the indoor temperature corresponding to the time-series air conditioning capacity based on the time-series air conditioning capacity and the room temperature prediction model, and outputs the predicted transition of the indoor temperature.

6. An air conditioning system comprising: an air conditioner; and the control system according to any one of Claims 1 to 3.

7. A control method of an air conditioner, the control method comprising: a step of receiving a setting of a target temperature and a specified time at which the target temperature is to be achieved; a step of calculating time-series air conditioning capacity of the air conditioner such that power consumption of the air conditioner for achieving the target temperature at the specified time is minimized; and a step of operating the air conditioner based on the time-series air conditioning capacity.

8. A program causing a computer to execute: a step of receiving a setting of a target temperature and a specified time at which the target temperature is to be achieved; a step of calculating time-series air conditioning capacity of an air conditioner such that power consumption of the air conditioner for achieving the target temperature at the specified time is minimized; and a step of operating the air conditioner based on the time-series air conditioning capacity.

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